# why too many epochs will cause overfitting?

I am reading the 《deep learning with python》. In chapter 4, about Fighting overfitting, I have two questions.

1. why increasing epochs may cause overfitting? I know increasing will cause more gradient descent, will more gradient descent can cause overfitting?

2. During the process of fighting overfitting, will the accuracy be reduced ?

• It's not guaranteed that you overfit. However, typically you start with an overparameterised network ( too many hidden units), but initialised around zero so no effect.. increasing epochs will mean you fit better and better to training data. Checking the validation data allows you to see whether performance on unseen data is also improving ( on average). It's quite possible that performance for part of input space improves for training and validation,and for other parts improves only for training, gets worse for validation – seanv507 Dec 27 '18 at 9:48